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Stem cell differentiation as a non-Markov stochastic process

Stem cell differentiation as a non-Markov stochastic process
Stem cell differentiation as a non-Markov stochastic process
Pluripotent stem cells can self-renew in culture and differentiate along all somatic lineages in vivo. While much is known about the molecular basis of pluripotency, the mechanisms of differentiation remain unclear. Here, we profile individual mouse embryonic stem cells as they progress along the neuronal lineage. We observe that cells pass from the pluripotent state to the neuronal state via an intermediate epiblast-like state. However, analysis of the rate at which cells enter and exit these observed cell states using a hidden Markov model indicates the presence of a chain of unobserved molecular states that each cell transits through stochastically in sequence. This chain of hidden states allows individual cells to record their position on the differentiation trajectory, thereby encoding a simple form of cellular memory. We suggest a statistical mechanics interpretation of these results that distinguishes between functionally distinct cellular ‘macrostates’ and functionally similar molecular ‘microstates’, and propose a model of stem cell differentiation as a non-Markov stochastic process.
2405-4712
268-282.e7
Stumpf, Patrick
dfdb286c-b321-46d3-8ba2-85b3b4a7f092
Smith, Rosanna C.G.
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Lenz, Michael
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Schuppert, Andreas, A.
62f9eb46-e8ed-424b-a4ae-9dadd63f8a31
Muller, Franz-Josef
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Babtie, Ann
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Chan, Thalia E.
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Stumpf, Michael P.H.
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Please, Colin P.
118dffe7-4b38-4787-a972-9feec535839e
Howison, Sam D.
5cce2c2e-abd3-4878-8a42-e471bfc966de
Arai, Fumio
55b7859b-98f0-450a-b355-74e1f1e1945d
Macarthur, Benjamin D.
2c0476e7-5d3e-4064-81bb-104e8e88bb6b
Stumpf, Patrick
dfdb286c-b321-46d3-8ba2-85b3b4a7f092
Smith, Rosanna C.G.
1fe5586f-92e9-4658-bd55-cd3eaa176b66
Lenz, Michael
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Schuppert, Andreas, A.
62f9eb46-e8ed-424b-a4ae-9dadd63f8a31
Muller, Franz-Josef
14203be1-092e-47ae-a023-d4c798adc449
Babtie, Ann
633b7500-61dc-4f8e-977a-2831951c5775
Chan, Thalia E.
705579a4-008e-4b9e-b7e4-506d839a0072
Stumpf, Michael P.H.
8320fd41-8650-4438-92aa-0b70ebf7cc00
Please, Colin P.
118dffe7-4b38-4787-a972-9feec535839e
Howison, Sam D.
5cce2c2e-abd3-4878-8a42-e471bfc966de
Arai, Fumio
55b7859b-98f0-450a-b355-74e1f1e1945d
Macarthur, Benjamin D.
2c0476e7-5d3e-4064-81bb-104e8e88bb6b

Stumpf, Patrick, Smith, Rosanna C.G., Lenz, Michael, Schuppert, Andreas, A., Muller, Franz-Josef, Babtie, Ann, Chan, Thalia E., Stumpf, Michael P.H., Please, Colin P., Howison, Sam D., Arai, Fumio and Macarthur, Benjamin D. (2017) Stem cell differentiation as a non-Markov stochastic process. Cell Systems, 5 (3), 268-282.e7. (doi:10.1016/j.cels.2017.08.009).

Record type: Article

Abstract

Pluripotent stem cells can self-renew in culture and differentiate along all somatic lineages in vivo. While much is known about the molecular basis of pluripotency, the mechanisms of differentiation remain unclear. Here, we profile individual mouse embryonic stem cells as they progress along the neuronal lineage. We observe that cells pass from the pluripotent state to the neuronal state via an intermediate epiblast-like state. However, analysis of the rate at which cells enter and exit these observed cell states using a hidden Markov model indicates the presence of a chain of unobserved molecular states that each cell transits through stochastically in sequence. This chain of hidden states allows individual cells to record their position on the differentiation trajectory, thereby encoding a simple form of cellular memory. We suggest a statistical mechanics interpretation of these results that distinguishes between functionally distinct cellular ‘macrostates’ and functionally similar molecular ‘microstates’, and propose a model of stem cell differentiation as a non-Markov stochastic process.

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Accepted/In Press date: 7 August 2017
e-pub ahead of print date: 27 September 2017
Published date: 27 September 2017

Identifiers

Local EPrints ID: 416970
URI: http://eprints.soton.ac.uk/id/eprint/416970
ISSN: 2405-4712
PURE UUID: 380a9766-46e9-45e8-b2ec-db42b3f43613
ORCID for Patrick Stumpf: ORCID iD orcid.org/0000-0003-0862-0290
ORCID for Benjamin D. Macarthur: ORCID iD orcid.org/0000-0002-5396-9750

Catalogue record

Date deposited: 15 Jan 2018 17:31
Last modified: 16 Mar 2024 05:42

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Contributors

Author: Patrick Stumpf ORCID iD
Author: Rosanna C.G. Smith
Author: Michael Lenz
Author: Andreas, A. Schuppert
Author: Franz-Josef Muller
Author: Ann Babtie
Author: Thalia E. Chan
Author: Michael P.H. Stumpf
Author: Colin P. Please
Author: Sam D. Howison
Author: Fumio Arai

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